Clinical analysis of 132 cases COVID-19 from Wuhan.

Numerous cases of pneumonia from a novel coronavirus (SARS-CoV-2) emerged in Wuhan, China during December 2019.We determined the correlations of patient parameters with disease severity in patients with COVID-19.A total of 132 patients from Wuhan Fourth Hospital who had COVID-19 from February 1 to February 29 in 2020 were retrospectively analyzed.Ninety patients had mild disease, 32 had severe disease, and 10 had critical disease. The severe/critical group was older (P < .05), had a higher proportion of males (P < .05), and had a greater mortality rate (0% vs 61.9%, P < .05). The main symptoms were fever (n = 112, 84.8%) and cough (n = 96, 72.7%). Patients were treated with antiviral agents (n = 94, 71.2%), antibiotics (n = 92, 69.7%), glucocorticoids (n = 46, 34.8%), intravenous immunoglobulin (n = 38, 27.3%), and/or traditional Chinese medicine (n = 40, 30.3%). Patients in the severe/critical group received mechanical ventilation (n = 22, 16.7%) or high-flow nasal can-nula oxygen therapy (n = 6, 4.5%). Chest computed tomography (CT) indicated bilateral pneumonia in all patients. Relative to the mild group, the severe/critical group had higher levels of leukocytes, C-reactive protein (CRP), procalcitonin (PCT), D-dimer, B-type natriuretic peptide (BNP), liver enzymes, and myocardial enzymes (P < .05), and decreased levels of lymphocytes and blood oxygen partial pressure (P < .05).The main clinical symptoms of patients from Wuhan who had COVID-19 were fever and cough. Patients with severe/critical disease were more likely to be male and elderly. Disease severity correlated with increased leukocytes, CRP, PCT, BNP, D-dimer, liver enzymes, and myocardial enzymes, and with decreased lymphocytes and blood oxygen partial pressure.

Spatial genetic structure of 2009 H1N1 pandemic influenza established as a result of interaction with human populations in mainland China.

Identifying the spatial patterns of genetic structure of influenza A viruses is a key factor for understanding their spread and evolutionary dynamics. In this study, we used phylogenetic and Bayesian clustering analyses of genetic sequences of the A/H1N1pdm09 virus with district-level locations in mainland China to investigate the spatial genetic structure of the A/H1N1pdm09 virus across human population landscapes. Positive correlation between geographic and genetic distances indicates high degrees of genetic similarity among viruses within small geographic regions but broad-scale genetic differentiation, implying that local viral circulation was a more important driver in the formation of the spatial genetic structure of the A/H1N1pdm09 virus than even, countrywide viral mixing and gene flow. Geographic heterogeneity in the distribution of genetic subpopulations of A/H1N1pdm09 virus in mainland China indicates both local to local transmission as well as broad-range viral migration. This combination of both local and global structure suggests that both small-scale and large-scale population circulation in China is responsible for viral genetic structure. Our study provides implications for understanding the evolution and spread of A/H1N1pdm09 virus across the population landscape of mainland China, which can inform disease control strategies for future pandemics.

[Changes in Secondary Inorganic Ions in PM2.5 at Different Pollution Stages Before and After COVID-19 Control].

To investigate the change characteristics of secondary inorganic ions in PM2.5 at different pollution stages before and after COVID-19, the online monitoring of winter meteorological and atmospheric pollutant concentrations in Zhengzhou from December 15, 2019 to February 15, 2020 was conducted using a high-resolution (1 h) online instrument. This study analyzed the causes of the haze process of COVID-19, the diurnal variation characteristics of air pollutants, and the distribution characteristics of air pollutants at different stages of haze.The results showed that Zhengzhou was mainly controlled by the high-pressure ridge during the haze process, and the weather situation was stable, which was conducive to the accumulation of air pollutants. SNA was the main component of water-soluble ions, accounting for more than 90%. Home isolation measures during COVID-19 had different impacts on the distribution characteristics of air pollutants in different haze stages. After COVID-19, the concentration of PM2.5 in the clean, occurrence, and dissipation stages increased compared with that before COVID-19 but significantly decreased in the development stage. The home isolation policy significantly reduced the high value of PM2.5. The concentrations of NO2, SO2, NH3, and CO were the highest in the haze development stage, showing a trend of first increasing and then decreasing. The concentration of O3 was lowest in the pre-COVID-19 development stage but highest in the post-COVID-19 development stage. The linear correlation between[NH4+]/[SO42-] and[NO3-]/[SO42-] at different time periods before and after COVID-19 was strong, indicating that the home isolation policy of COVID-19 did not change the generation mode of NO3-, and the corresponding reaction was always the main generation mode of NO3-. The correlation between[excess-NH4+] and[NO3-] was high in different periods before COVID-19, and NO3- generation was related to the increase in NH3 or NH4+ in the process of PM2.5 pollution in Zhengzhou.

Imported malaria from land bordering countries in China: A challenge in preventing the reestablishment of malaria transmission.

OBJECTIVE: No indigenous malaria cases have been reported since 2017 in China, but a large number of imported cases are still reported every year, including those from the land bordering countries. To characterize their epidemiological profiles will provide evidence for the development of appropriate strategies to effectively address the challenges of border malaria in the post-elimination phase. METHODS: Individual-level data of imported malaria cases from the land bordering countries were collected from 2017 to 2021 in China via the web-based surveillance systems, and analyzed by SPSS, ArcGIS and WPS software, to explore their epidemiological profiles. RESULTS: A total of 1170 malaria cases imported into China from six of the fourteen land bordering countries were reported between 2017 and 2021 with a decline trend. Overall, cases were widely distributed in 31-97 counties from 11 to 21 provinces but mainly in Yunnan. Moreover, these imported cases were mainly infected with P. vivax (94.8%), and a total of 68 recurrent cases were reported in 6-14 counties from 4 to 8 provinces. In addition, nearly 57.1% of the total reported cases could seek healthcare within 2 days of getting sick, and 71.3% of the reported cases could be confirmed as malaria on the day they sought medical care. CONCLUSIONS: China still needs to attach great importance to the risk and challenge of the imported malaria from bordering countries particularly from Myanmar in preventing reestablishment of malaria transmission in the post-elimination phase. It is necessary not only to strengthen collaboration and cooperation with the bordering countries, but also coordinate multiple departments at home to improve malaria surveillance and response system and prevent the reestablishment of malaria transmission in China.

Real-time risk ranking of emerging epidemics based on optimized moving average prediction limit-taking the COVID-19 pandemic as an example.

BACKGROUND: Mathematical models to forecast the risk trend of the COVID-19 pandemic timely are of great significance to control the pandemic, but the requirement of manual operation and many parameters hinders their efficiency and value for application. This study aimed to establish a convenient and prompt one for monitoring emerging infectious diseases online and achieving risk assessment in real time. METHODS: The Optimized Moving Average Prediction Limit (Op-MAPL) algorithm model analysed real-time COVID-19 data online and was validated using the data of the Delta variant in India and the Omicron in the United States. Then, the model was utilized to determine the infection risk level of the Omicron in Shanghai and Beijing. RESULTS: The Op-MAPL model can predict the epidemic peak accurately. The daily risk ranking was stable and predictive, with an average accuracy of 87.85% within next 7 days. Early warning signals were issued for Shanghai and Beijing on February 28 and April 23, 2022, respectively. The two cities were rated as medium-high risk or above from March 27 to April 20 and from April 24 to May 5, indicating that the pandemic had entered a period of rapid increase. After April 21 and May 26, the risk level was downgraded to medium and became stable by the algorithm, indicating that the pandemic had been controlled well and mitigated gradually. CONCLUSIONS: The Op-MAPL relies on nothing but an indicator to assess the risk level of the COVID-19 pandemic with different data sources and granularities. This forward-looking method realizes real-time monitoring and early warning effectively to provide a valuable reference to prevent and control infectious diseases.

The mediating role of psychological capital in the association between life satisfaction and depressive and anxiety symptoms among Chinese medical students during the COVID-19 pandemic: a cross-sectional study.

BACKGROUND: Although life satisfaction is a predictor of depressive and anxiety symptoms, the mechanisms underlying this association are poorly understood. This study examined how psychological capital (PsyCap), a positive psychological state, mediated the association between life satisfaction and depressive and anxiety symptoms among Chinese medical students during the COVID-19 pandemic. METHODS: A cross-sectional survey was conducted at three medical universities in China. A self-administered questionnaire was distributed to 583 students. Depressive symptoms, anxiety symptoms, life satisfaction, and PsyCap were measured anonymously. A hierarchical linear regression analysis was performed to explore the effects of life satisfaction on depressive and anxiety symptoms. Asymptotic and resampling strategies were used to examine how PsyCap mediates the association between life satisfaction and depressive and anxiety symptoms. RESULTS: Life satisfaction was positively associated with PsyCap and its four components. There were significant negative associations between life satisfaction, psychological capital, resilience, optimism, and depressive and anxiety symptoms among medical students. Self-efficacy was negatively associated with depressive and anxiety symptoms. Psychological capital (a×b = -0.3201, BCa 95% CI: -0.3899, -0.2446; a×b = -0.2749, BCa 95% CI: -0.3817, -0.1996), resilience (a×b = -0.2103, BCa 95% CI: -0.2727, -0.1580; a×b = -0.1871, BCa 95% CI: -0.2520, -0.1414), optimism (a×b = -0.2100, BCa 95% CI: -0.3388, -0.1150; a×b = -0.1998, BCa 95% CI: -0.3307, -0.0980), and self-efficacy (a×b = -0.0916, BCa 95% CI: 0.0048, 0.11629; a×b = 0.1352, BCa 95% CI: 0.0336, 0.2117) significantly mediated the association between life satisfaction and depressive and anxiety symptoms. LIMITATIONS: This was a cross-sectional study, and causal relationships between the variables could not be ascertained. Self-reported questionnaire instruments were used for data collection, which may have recall bias. CONCLUSIONS: Life satisfaction and PsyCap can be used as positive resources to reduce depressive and anxiety symptoms among third-year Chinese medical students during the COVID-19 pandemic. Psychological capital and its components (self-efficacy, resilience, and optimism) partially mediated the relationship between life satisfaction and depressive symptoms, and completely mediated the relationship between life satisfaction and anxiety symptoms. Therefore, improving life satisfaction and investing in psychological capital (especially self-efficacy, resilience, and optimism) should be included in the prevention and treatment of depressive and anxiety symptoms among third-year Chinese medical students. Additional attention is needed to pay for self-efficacy in such disadvantageous contexts.

Threshold conditions for curbing COVID-19 with a dynamic zero-case policy derived from 101 outbreaks in China.

By 31 May 2022, original/Alpha, Delta and Omicron strains induced 101 outbreaks of COVID-19 in mainland China. Most outbreaks were cleared by combining non-pharmaceutical interventions (NPIs) with vaccines, but continuous virus variations challenged the dynamic zero-case policy (DZCP), posing questions of what are the prerequisites and threshold levels for success? And what are the independent effects of vaccination in each outbreak? Using a modified classic infectious disease dynamic model and an iterative relationship for new infections per day, the effectiveness of vaccines and NPIs was deduced, from which the independent effectiveness of vaccines was derived. There was a negative correlation between vaccination coverage rates and virus transmission. For the Delta strain, a 61.8% increase in the vaccination rate (VR) reduced the control reproduction number (CRN) by about 27%. For the Omicron strain, a 20.43% increase in VR, including booster shots, reduced the CRN by 42.16%. The implementation speed of NPIs against the original/Alpha strain was faster than the virus's transmission speed, and vaccines significantly accelerated the DZCP against the Delta strain. The CRN ([Formula: see text]) during the exponential growth phase and the peak time and intensity of NPIs were key factors affecting a comprehensive theoretical threshold condition for DZCP success, illustrated by contour diagrams for the CRN under different conditions. The DZCP maintained the [Formula: see text] of 101 outbreaks below the safe threshold level, but the strength of NPIs was close to saturation especially for Omicron, and there was little room for improvement. Only by curbing the rise in the early stage and shortening the exponential growth period could clearing be achieved quickly. Strengthening China's vaccine immune barrier can improve China's ability to prevent and control epidemics and provide greater scope for the selection and adjustment of NPIs. Otherwise, there will be rapid rises in infection rates and an extremely high peak and huge pressure on the healthcare system, and a potential increase in excess mortality.

An Online Survey on the Relationship Between Positive Coping and Post-Traumatic Stress Symptoms (PTSS) of Medical Students in China During the COVID-19 Pandemic: The Mediating Role of Social Support.

BACKGROUND The COVID-19 pandemic has caused varying degrees of psychological stress among medical students. This research explored the post-traumatic stress symptoms (PTSS) of medical students in China and their relationship with positive coping and social support. MATERIAL AND METHODS In the form of cross-sectional online survey, 2280 medical students locked down at home were selected by random cluster method to investigate social support, coping style, and PTSS using the Social Support Rating Scale (SSRS), Simplified Coping Style Questionnaire (SCSQ), and Post-traumatic Stress Disorder (PTSD) Checklist-Civilian Version (PCL-C), respectively. RESULTS This research found that the PTSS detection rate in medical students was 10.42% during the COVID-19 pandemic. The PTSS scores of females were significantly higher than that of the males. However, the PTSS detection rate in females (9.71%) was not significantly different from that in males (11.24%). Compared with those of the non-PTSS group, the total score and its all-factor score of social support, the total score of coping style and the positive coping score of the PTSS group were much lower, while the negative coping score of the PTSS group was much higher (P<0.01). Positive coping was positively correlated with social support, while positive coping and social support were negatively correlated with PTSS. The total effect of positive coping on PTSS was -0.310 (P<0.001), the direct effect was -0.128 (P<0.01), and the indirect effect was -0.182 (P<0.001). Social support played a mediating role between positive coping and PTSS, with the mediating effect accounting for 58.81% of the total effect. CONCLUSIONS Social support plays a mediating role between positive coping and post-traumatic stress symptoms. Objective support and positive coping are the 2 main protective factors of PTSS.

Prevalence of respiratory pathogens and risk of developing pneumonia under non-pharmaceutical interventions in Suzhou, China.

This study aims to evaluate the impact of non-pharmaceutical interventions (NPIs) on the prevalence of respiratory pathogens among hospitalised children with acute respiratory infections (ARIs) in Suzhou. Children with ARIs admitted to the Children's Hospital of Soochow University between 1 September 2021 and 31 December 2022 and subjected to 13 respiratory pathogen multiplex PCR assays were included in the study. We retrospectively collected demographic details, results of respiratory pathogen panel tests, and discharge diagnostic information of the participants, and described the age and seasonal distribution of respiratory pathogens and risk factors for developing pneumonia. A total of 10,396 children <16 years of age, including 5,905 males and 4,491 females, were part of the study. The positive rates of the 11 respiratory pathogen assays were 23.3% (human rhinovirus (HRV)), 15.9% (human respiratory syncytial virus (HRSV)), 10.5% (human metapneumovirus (HMPV)), 10.3% (human parainfluenza virus (HPIV)), 8.6% (mycoplasma pneumoniae (MP)), 5.8% (Boca), 3.5% (influenza A (InfA)), 2.9% (influenza B (InfB)), 2.7% (human coronavirus (HCOV)), 2.0% (adenovirus (ADV)), and 0.5% (Ch), respectively. Bocavirus and HPIV detection peaked during the period from September to November (autumn), and MP and HMPV peaked in the months of November and December. The peak of InfA detection was found to be in summer (July and August), whereas the InfB peak was observed to be in winter (December, January, and February). HRSV and HRV predominated in the <3 years age group. HRV and HMPV were common in the 3-6 years group, whereas MP was predominant in the ≥6 years group. MP (odds ratio (OR): 70.068, 95%CI: 32.665-150.298, P < 0.01), HMPV (OR: 6.493, 95%CI: 4.802-8.780, P < 0.01), Boca (OR: 3.300, 95%CI: 2.186-4.980, P < 0.01), and HRSV (OR: 2.649, 95%CI: 2.089-3.358, P < 0.01) infections were more likely to develop into pneumonia than the other pathogens. With the use of NPIs, HRV was the most common pathogen in children with ARIs, and MP was more likely to progress to pneumonia than other pathogens.

Spatial autocorrelation and heterogenicity of demographic and healthcare factors in the five waves of COVID-19 epidemic in Thailand.

A study of 2,569,617 Thailand citizens diagnosed with COVID-19 from January 2020 to March 2022 was conducted with the aim of identifying the spatial distribution pattern of incidence rate of COVID-19 during its five main waves in all 77 provinces of the country. Wave 4 had the highest incidence rate (9,007 cases per 100,000) followed by the Wave 5, with 8,460 cases per 100,000. We also determined the spatial autocorrelation between a set of five demographic and health care factors and the spread of the infection within the provinces using Local Indicators of Spatial Association (LISA) and univariate and bivariate analysis with Moran's I. The spatial autocorrelation between the variables examined and the incidence rates was particularly strong during the waves 3-5. All findings confirmed the existence of spatial autocorrelation and heterogenicity of COVID-19 with the distribution of cases with respect to one or several of the five factors examined. The study identified significant spatial autocorrelation with regard to the COVID-19 incidence rate with these variables in all five waves. Depending on which province that was investigated, strong spatial autocorrelation of the High-High pattern was observed in 3 to 9 clusters and of the Low-Low pattern in 4 to 17 clusters, whereas negative spatial autocorrelation was observed in 1 to 9 clusters of the High-Low pattern and in 1 to 6 clusters of Low-High pattern. These spatial data should support stakeholders and policymakers in their efforts to prevent, control, monitor and evaluate the multidimensional determinants of the COVID-19 pandemic.

Special Issue: "Respiratory Disease in the COVID-19 Era".

The outbreak of the viral infection known as coronavirus disease 2019 (COVID-19), caused by the novel pathogen severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), was first reported in Wuhan, China, in December 2019 [...].

HPV prevalence and genotype distribution among women in eastern China during the Covid-19 pandemic.

Since March 2020, the pandemic caused by SARS-CoV-2 has affected nearly all aspects of daily life. In this study, we investigated the age-stratified prevalence and genotype distribution of human papillomavirus (HPV) among females in Shandong province (eastern China) and aimed to provide guidance on HPV-based cervical cancer screening and vaccination. The distribution of HPV genotypes was analyzed using PCR-Reverse Dot Hybridization. The overall infection rate of HPV was 16.4%, which was dominated by high-risk genotypes. The most prevalent genotype was HPV16 (2.9%), followed by HPV52 (2.3%), HPV53 (1.8%), HPV58 (1.5%), and HPV51 (1.3%). Among the positive cases with HPV infection, single-genotype infection was significantly higher than that of multi-genotype infection. In subgroup analyses by age (≤25, 26-35, 36-45, 46-55, >55), HPV16, 52, and 53 were consistently the three most common hrHPV genotypes in all age groups. The infection rate of multi-genotypes in the ≤25 and >55 age groups was significantly higher than that in other age groups. A bimodal distribution of HPV infection rate was observed in different age groups. Among lrHPV genotypes, HPV6, HPV11, and HPV81 were the three most common types in the ≤25 age group, while in other age groups, HPV81, HPV42, and HPV43 are the three most common lrHPV genotypes. This study provides basic information on the distribution and genotypes of HPV in the female population in eastern China, which could improve the application of HPV diagnostic probes and vaccines.

The Role of "Hierarchical and Classified Prevention and Control Measures (HCPC)" Strategy for SARS-CoV-2 Delta Variant in Guangzhou: A Modeling Study.

BACKGROUND: The Delta variant of SARS-COV-2 has replaced previously circulating strains around the world in 2021. Sporadic outbreaks of the Delta variant in China have posed a concern about how to properly respond to the battle against evolving COVID-19. Here, we analyzed the "hierarchical and classified prevention and control (HCPC)" measures strategy deployed during the recent Guangzhou outbreak. METHODS: A modified susceptible-exposed-pre-symptomatic-infectious-recovered (SEPIR) model was developed and applied to study a range of different scenarios to evaluate the effectiveness of policy deployment. We simulated severe different scenarios to understand policy implementation and timing of implementation. Two outcomes were measured: magnitude of transmission and duration of transmission. The outcomes of scenario evaluations were presented relative to the reality case (i.e., 368 cases in 34 days) with 95% confidence interval (CI). RESULTS: Based on our simulation, the outbreak would become out of control with 7 million estimated infections under the assumption of the absence of any interventions than the 153 reported cases in reality in Guangzhou. The simulation on delayed implementation of interventions showed that the total case numbers would also increase by 166.67%-813.07% if the interventions were delayed by 3 days or 7 days. CONCLUSIONS: It may be concluded that timely and more precise interventions including mass testing and graded community management are effective measures for Delta variant containment in China.

Comparison of Antibiotic Resistance Profiles of Salmonella Isolates from Retail Meats in Nanchang, China, in Two Periods.

Salmonella is one of the most important foodborne pathogens. In this article, a total of 160 Salmonella isolates recovered from retail meats in June-July 2018 (before COVID-19 outbreak) and December 2020-April 2021 (after COVID-19 outbreak) in Nanchang, China, were characterized for serotyping, antimicrobial susceptibility, and specific resistance gene screening. The prevalence of Salmonella Typhimurium increased from 5.4% in 2018 to 19.1% in 2021, and Salmonella Enteritidis increased from 3.3% in 2018 to 8.8% in 2021. Compared with those in June-July 2018, Salmonella isolates in December 2020-April 2021 demonstrated a significant increase in resistance to 13 tested antibiotics except for doxycycline and nitrofurantoin (p < 0.05). The Salmonella isolates in December 2020-April 2021 showed a higher presence of plasmid-mediated quinolone resistance genes (qnrA, qnrB, and qnrS), and mutations in the quinolone resistance-determining region (gyrA Asp87Asn, gyrA Asp87Tyr, parC Thr57Ser, and parC Ser80Ile). Whole-genome sequencing was used to analyze four polymyxin B-resistant strains. Some common mutation sites in eptC and micA were found in the four strains. Based on the data in this article, it indicated that antibiotic resistance was facilitated and more gene mutations related to quinolone resistance were developed.

Sleep disturbance and anxiety symptoms among asymptomatic COVID-19 carriers in Shanghai, China: the mediating role of entrapment and defeat.

BACKGROUND: The COVID-19 pandemic increases the risk of psychological problems, especially for the infected population. Sleep disturbance and feelings of defeat and entrapment are well-documented risk factors of anxiety symptoms. Exploring the psychological mechanism of the development of anxiety symptoms is essential for effective prevention. This study aimed to examine the mediating effects of entrapment and defeat in the association between sleep disturbance and anxiety symptoms among asymptomatic COVID-19 carriers in Shanghai, China. METHODS: A cross-sectional study was conducted from March to April, 2022. Participants were 1,283 asymptomatic COVID-19 carriers enrolled from the Ruijin Jiahe Fangcang Shelter Hospital, Shanghai (59.6% male; mean age = 39.6 years). Questionnaire measures of sleep disturbance, entrapment, defeat, anxiety symptoms, and background characteristics were obtained. A mediation model was constructed to test the mediating effects of entrapment and defeat in the association between sleep disturbance and anxiety symptoms. RESULTS: The prevalence rates of sleep disturbance and anxiety symptoms were 34.3% and 18.8%. Sleep disturbance was positively associated with anxiety symptoms (OR [95%CI] = 5.013 [3.721-6.753]). The relationship between sleep disturbance and anxiety symptoms (total effect: Std. Estimate = 0.509) was partially mediated by entrapment (indirect effect: Std. Estimate = 0.129) and defeat (indirect effect: Std. Estimate = 0.126). The mediating effect of entrapment and defeat accounted for 50.3% of the association between sleep disturbance and anxiety symptoms. CONCLUSION: Sleep disturbance and anxiety symptoms were prevalent among asymptomatic COVID-19 carriers. Entrapment and defeat mediate the association between sleep disturbance and anxiety symptoms. More attention is needed to monitoring sleep conditions and feelings of defeat and entrapment to reduce the risk of anxiety.

The indirect impacts of nonpharmacological COVID-19 control measures on other infectious diseases in Yinchuan, Northwest China: a time series study.

BACKGROUND: Various nonpharmaceutical interventions (NPIs) against COVID-19 continue to have an impact on socioeconomic and population behaviour patterns. However, the effect of NPIs on notifiable infectious diseases remains inconclusive due to the variability of the disease spectrum, high-incidence endemic diseases and environmental factors across different geographical regions. Thus, it is of public health interest to explore the influence of NPIs on notifiable infectious diseases in Yinchuan, Northwest China. METHODS: Based on data on notifiable infectious diseases (NIDs), air pollutants, meteorological data, and the number of health institutional personnel in Yinchuan, we first fitted dynamic regression time series models to the incidence of NIDs from 2013 to 2019 and then estimated the incidence for 2020. Then, we compared the projected time series data with the observed incidence of NIDs in 2020. We calculated the relative reduction in NIDs at different emergency response levels in 2020 to identify the impacts of NIPs on NIDs in Yinchuan. RESULTS: A total of 15,711 cases of NIDs were reported in Yinchuan in 2020, which was 42.59% lower than the average annual number of cases from 2013 to 2019. Natural focal diseases and vector-borne infectious diseases showed an increasing trend, as the observed incidence in 2020 was 46.86% higher than the estimated cases. The observed number of cases changed in respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases were 65.27%, 58.45% and 35.01% higher than the expected number, respectively. The NIDs with the highest reductions in each subgroup were hand, foot, and mouth disease (5854 cases), infectious diarrhoea (2157 cases) and scarlet fever (832 cases), respectively. In addition, it was also found that the expected relative reduction in NIDs in 2020 showed a decline across different emergency response levels, as the relative reduction dropped from 65.65% (95% CI: -65.86%, 80.84%) during the level 1 response to 52.72% (95% CI: 20.84%, 66.30%) during the level 3 response. CONCLUSIONS: The widespread implementation of NPIs in 2020 may have had significant inhibitory effects on the incidence of respiratory infectious diseases, intestinal infectious diseases and sexually transmitted or bloodborne diseases. The relative reduction in NIDs during different emergency response levels in 2020 showed a declining trend as the response level changed from level 1 to level 3. These results can serve as essential guidance for policy-makers and stakeholders to take specific actions to control infectious diseases and protect vulnerable populations in the future.

Mortality burden due to ambient nitrogen dioxide pollution in China: Application of high-resolution models.

BACKGROUND: A large gap exists between the latest Global Air Quality Guidelines (AQG 2021) and Chinese air quality standards for NO2. Assessing whether and to what extent air quality standards for NO2 should be tightened in China requires a comprehensive understanding of the spatiotemporal characteristics of population exposure to ambient NO2 and related health risks, which have not been studied to date. OBJECTIVE: We predicted ground NO2 concentrations with high resolution in mainland China, explored exposure characteristics to NO2 pollution, and assessed the mortality burden attributable to NO2 exposure. METHODS: Daily NO2 concentrations in 2019 were predicted at 1-km spatial resolution in mainland China using random forest models incorporating multiple predictors. From these high-resolution predictions, we explored the spatiotemporal distribution of NO2, population and area percentages with NO2 exposure exceeding criterion levels, and premature deaths attributable to long- and short-term NO2 exposure in China. RESULTS: The cross-validation R2and root mean squared error of the NO2 predicting model were 0.80 and 7.78 µg/m3, respectively,at the daily level in 2019.The percentage of people (population number) with annual NO2 exposure over 40 µg/m3 in mainland China in 2019 was 10.40 % (145,605,200), and it reached 99.68 % (1,395,569,840) with the AQG guideline value of 10 µg/m3. NO2 levels and population exposure risk were elevated in urban areas than in rural. Long- and short-term exposures to NO2 were associated with 285,036 and 121,263 non-accidental deaths, respectively, in China in 2019. Tightening standards in steps gradually would increase the potential health benefit. CONCLUSION: In China, NO2 pollution is associated with significant mortality burden. Spatial disparities exist in NO2 pollution and exposure risks. China's current air quality standards may no longer objectively reflect the severity of NO2 pollution and exposure risk. Tightening the national standards for NO2 is needed and will lead to significant health benefits.

Cost-effectiveness analysis of COVID-19 screening strategy under China's dynamic zero-case policy.

This study aims to optimize the COVID-19 screening strategies under China's dynamic zero-case policy through cost-effectiveness analysis. A total of 9 screening strategies with different screening frequencies and combinations of detection methods were designed. A stochastic agent-based model was used to simulate the progress of the COVID-19 outbreak in scenario I (close contacts were promptly quarantined) and scenario II (close contacts were not promptly quarantined). The primary outcomes included the number of infections, number of close contacts, number of deaths, the duration of the epidemic, and duration of movement restriction. Net monetary benefit (NMB) and the incremental cost-benefit ratio were used to compare the cost-effectiveness of different screening strategies. The results indicated that under China's COVID-19 dynamic zero-case policy, high-frequency screening can help contain the spread of the epidemic, reduce the size and burden of the epidemic, and is cost-effective. Mass antigen testing is not cost-effective compared with mass nucleic acid testing in the same screening frequency. It would be more cost-effective to use AT as a supplemental screening tool when NAT capacity is insufficient or when outbreaks are spreading very rapidly.